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The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
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Abstract
Motivated by the rapid spread of coronavirus disease 2019 (COVID-19) in mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated on the basis of internationally reported cases and shows that, at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in mainland China but had a more marked effect on the international scale, where case importations were reduced by nearly 80% until mid-February. Modeling results also indicate that sustained 90% travel restrictions to and from mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
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“Most of the studies reviewed acknowledged that quarantine is one of the first public health measures to control and prevent further spread of respirational infections caused by the coronavirus (3, 11, 14, 22).”
From Definitions and psychological impacts of quarantine and strategies to reduce it: A review paper (2020) · cites this paper as [14]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These studies referred to travel restrictions as travel quarantine, which included the restriction or cancellation of overland air travel and public and private vehicles to areas of a high risk of the outbreak (14).”
From Definitions and psychological impacts of quarantine and strategies to reduce it: A review paper (2020) · cites this paper as [14]
Experimental — accuracy not yet measuredIn the citing paper
“Using disease simulation on aggregated inter-province movement counts in China as derived from Baidu location based services [101] has shown that the travel restrictions in Wuhan introduced on 23 January 2020 had reduced the number of cases exported internationally by 70–80% until mid February 2020.”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [101]
In the citing paper
“Several studies across different countries have shown their effectiveness [101,102].”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [101]
In the citing paper
“Affected travelers are required to undergo compulsory self-quarantine for 14 days (Chinazzi et al., 2020) before any test of swab is issued.”
From IoMT amid COVID-19 pandemic: Application, architecture, technology, and security (2021) · cites this paper as Chinazzi et al., 2020
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Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Correspondence - Tranexamic acid for traumatic brain injury
(2005) · London School of Economics and Political Science Theses Online (London School of Economics and Political Science) · doi:10.1016/s0140-6736 · Cited by 11,894
Wu, J. T., Leung, K., & Leung, G. M. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30260-9 · Cited by 4,389
Tian, H., Liu, Y., Li, Y., Wu, C.-H., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., et al. (2020) · Science · doi:10.1126/science.abb6105 · Cited by 2,010
Zhao, S., Lin, Q., Ran, J., Musa, S. S., Yang, G., Wang, W., Lou, Y., Gao, D., Yang, L., He, D., et al. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.01.050 · Cited by 1,852
Backer, J. A., Klinkenberg, D., & Wallinga, J. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.5.2000062 · Cited by 1,546
Transmission Dynamics and Control of Severe Acute Respiratory Syndrome
Lipsitch, M., Cohen, T., Cooper, B. S., Robins, J. M., Ma, S., James, L., Gopalakrishna, G., Chew, S. K., Tan, C. C., Samore, M. H., et al. (2003) · Science · doi:10.1126/science.1086616 · Cited by 1,485
Riou, J., & Althaus, C. L. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.4.2000058 · Cited by 1,354
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Pan, A., Liu, L., Wang, C., Guo, H., Hao, X., Wang, Q., Huang, J., He, N., Yu, H., Lin, X., et al. (2020) · JAMA · doi:10.1001/jama.2020.6130 · Cited by 1,931
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Lai, S., Ruktanonchai, N., Zhou, L., Prosper, O., Luo, W. P., Floyd, J., Wesolowski, A., Santillana, M., Zhang, C., Du, X., et al. (2020) · Nature · doi:10.1038/s41586-020-2293-x · Cited by 1,357
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Budd, J., Miller, B. S., Manning, E. M., Lampos, V., Zhuang, M., Edelstein, M., Rees, G., Emery, V. C., Stevens, M. M., Keegan, N., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1011-4 · Cited by 1,195
Gilbert, M., Pullano, G., Pinotti, F., Valdano, E., Poletto, C., Boëlle, P., D’Ortenzio, É., Yazdanpanah, Y., Eholié, S. P., Altmann, M., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30411-6 · Cited by 1,216
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Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., Wu, Q., Merler, S., Viboud, C., Vespignani, A., et al. (2020) · Science · doi:10.1126/science.abb8001 · Cited by 1,107
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Jing, Q.-L., Liu, M.-J., Zhang, Z.-B., Fang, L.-Q., Yuan, J., Zhang, A.-R., Dean, N. E., Luo, L., Ma, M.-M., Longini, I. M., et al. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30471-0 · Cited by 492
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Farooq, A., Laato, S., & Islam, A. K. M. N. (2020) · Journal of Medical Internet Research · doi:10.2196/19128 · Cited by 467
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Pham, Q.-V., Nguyen, D. C., Huynh-The, T., Hwang, W.-J., & Pathirana, P. N. (2020) · IEEE Access · doi:10.1109/access.2020.3009328 · Cited by 413
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Liu, Y., Morgenstern, C., Kelly, J., Lowe, R., CMMID COVID-19 Working Group, & Jit, M. (2021) · BMC Medicine · doi:10.1186/s12916-020-01872-8 · Cited by 386
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Nkengasong, J. N., & Mankoula, W. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30464-5 · Cited by 374
Stawicki, S. P., Jeanmonod, R., Miller, A., Paladino, L., Gaieski, D. F., Yaffee, A. Q., Wulf, A. D., Grover, J., Papadimos, T. J., Bloem, C. M., et al. (2020) · Journal of Global Infectious Diseases · doi:10.4103/jgid.jgid_86_20 · Cited by 388
de Bruin, Y. B., Lequarré, A., McCourt, J., Clevestig, P., Pigazzani, F., Jeddi, M. Z., Colosio, C., & Goulart, M. (2020) · Safety Science · doi:10.1016/j.ssci.2020.104773 · Cited by 397
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Lecocq, T., Hicks, S., Noten, K. V., van Wijk, K., Koelemeijer, P., Plaen, R. S. M. D., Massin, F., Hillers, G., Anthony, R. E., Apoloner, M.-T., et al. (2020) · Science · doi:10.1126/science.abd2438 · Cited by 378
Signal propagation in complex networks
Ji, P., Ye, J., Mu, Y., Lin, W. J., Tian, Y., Hens, C., Perc, M., Tang, Y. S., Sun, J., & Kurths, J. (2023) · Physics Reports · doi:10.1016/j.physrep.2023.03.005 · Cited by 375
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Linka, K., Peirlinck, M., Costabal, F. S., & Ellen Kuhl, A. (2020) · Computer Methods in Biomechanics & Biomedical Engineering · doi:10.1080/10255842.2020.1759560 · Cited by 321
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Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (2020) · Scientific Data · doi:10.1038/s41597-020-00575-2 · Cited by 318
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Zhou, Y., Xu, R., Hu, D., Yue, Y., Li, Q., & Xia, J. (2020) · The Lancet Digital Health · doi:10.1016/s2589-7500(20)30165-5 · Cited by 285
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Metadata
- Authors
- Chinazzi, M., Davis, J. T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., Pastore y Piontti, A., Mu, K., Rossi, L., Sun, K., Viboud, C., Xiong, X., Yu, H., Halloran, M. E., Longini, I. M., & Vespignani, A.
- Affiliations
- Northeastern University (US)
- Fondazione Bruno Kessler (IT)
- Institute for Scientific Interchange (IT)
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
- National Institutes of Health (US)
- Fogarty International Center, NIH, Bethesda, MD, USA.
- Fudan University (CN)
- University of Washington (US)
- University of Florida Health (US)
- Corresponding author
- Longini, Ira M.
- Vespignani, Alessandro
- ORCID
- Venue
- Science
- Published
- 2020-04-24
- Volume
- 368
- Issue
- 6489
- Pages
- 395-400
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7164386
- OpenAlex
- W3010131837
- Cited by
- 3,694
- References
- 30
- Citations by year
- 2026: 87 · 2025: 173 · 2024: 244 · 2023: 405 · 2022: 644 · 2021: 1101 · 2020: 1036
- FWCI
- 127.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- U.S. Department of Health and Human Services
- National Institutes of Health (H2020, MIDAS-U54-GM111274)
- Horizon 2020 Framework Programme (EU‐H2020)
- National Institute of General Medical Sciences (U54GM111274)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Travel-related health issues
- Keywords
- COVID-19 pandemic, travel restrictions, metapopulation model, epidemic projection, international spread, quarantine, epidemic control
- MeSH terms
- Betacoronavirus, Communicable Diseases, Imported, COVID-19, SARS-CoV-2, China, Computer Simulation, Disease Outbreaks, Humans, Pneumonia, Viral, Quarantine, Travel, Models, Statistical, Incidence, Coronavirus Infections, Internationality, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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